Regional extreme value index estimation and a test of tail homogeneity

2015 ◽  
Vol 27 (2) ◽  
pp. 103-115 ◽  
Author(s):  
Paul Kinsvater ◽  
Roland Fried ◽  
Jona Lilienthal
Keyword(s):  
Extreme Value ◽  
Extreme Value Index ◽  
Index Estimation

Mean-of-order p reduced-bias extreme value index estimation under a third-order framework

Extremes ◽  
2016 ◽  
Vol 19 (4) ◽  
pp. 561-589 ◽  
Author(s):  
Frederico Caeiro ◽  
M. Ivette Gomes ◽  
Jan Beirlant ◽  
Tertius de Wet
Keyword(s):  
Extreme Value ◽  
Extreme Value Index ◽  
Third Order ◽  
Index Estimation

scholarly journals On Extreme Value Index Estimation under Random Censoring

2018 ◽  
Vol 5 (2) ◽  
pp. 419-445
Author(s):  
Richard Minkah ◽  
Tertius de Wet ◽  
Kwabena Doku-Amponsah
Keyword(s):  
Extreme Value ◽  
Extreme Value Index ◽  
Random Censoring ◽  
Index Estimation

scholarly journals Tail product-limit process for truncated data with application to extreme value index estimation

Extremes ◽  
2016 ◽  
Vol 19 (2) ◽  
pp. 219-251 ◽  
Author(s):  
Souad Benchaira ◽  
Djamel Meraghni ◽  
Abdelhakim Necir
Keyword(s):  
Extreme Value ◽  
Extreme Value Index ◽  
Truncated Data ◽  
Limit Process ◽  
Product Limit ◽  
Index Estimation

scholarly journals Extreme Value Index Estimation by Means of an Inequality Curve

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1834
Author(s):  
Emanuele Taufer ◽  
Flavio Santi ◽  
Pier Luigi Novi Inverardi ◽  
Giuseppe Espa ◽  
Maria Michela Dickson
Keyword(s):  
Real Data ◽  
Extreme Value ◽  
Extreme Value Index ◽  
Data Sets ◽  
Powerful Method ◽  
Estimation Strategy ◽  
Graphical Interpretation ◽  
Regularly Varying ◽  
Index Estimation

A characterizing property of Zenga (1984) inequality curve is exploited in order to develop an estimator for the extreme value index of a distribution with regularly varying tail. The approach proposed here has a nice graphical interpretation which provides a powerful method for the analysis of the tail of a distribution. The properties of the proposed estimation strategy are analysed theoretically and by means of simulations. The usefulness of the method will be tested also on real data sets.

Lehmer's mean-of-order-p extreme value index estimation: a simulation study and applications

2019 ◽  
Vol 47 (13-15) ◽  
pp. 2825-2845 ◽  
Author(s):  
Helena Penalva ◽  
M. Ivette Gomes ◽  
Frederico Caeiro ◽  
M. Manuela Neves
Keyword(s):  
Simulation Study ◽  
Extreme Value ◽  
Extreme Value Index ◽  
Index Estimation

scholarly journals Reduced-Bias Location-Invariant Extreme Value Index Estimation: A Simulation Study

2011 ◽  
Vol 40 (3) ◽  
pp. 424-447 ◽  
Author(s):  
M. Ivette Gomes ◽  
Lígia Henriques-Rodrigues ◽  
M. Cristina Miranda
Keyword(s):  
Simulation Study ◽  
Extreme Value ◽  
Extreme Value Index ◽  
Index Estimation

Optimal choice of kn-records in the extreme value index estimation

2005 ◽  
Vol 23 (2/2005) ◽  
Author(s):  
Mohamed El Arrouchi ◽  
Abdelouahid Imlahi
Keyword(s):  
Extreme Value ◽  
Optimal Choice ◽  
Extreme Value Index ◽  
Index Estimation
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